Detection and Recognition of Barriers in Egocentric Images for Safe Urban Sidewalks

Θεοδοσίου, Ζήνωνας; Partaourides, Harris; Panayi, Simoni; Kitsis, Andreas; Lanitis, Andreas

doi:10.1007/978-3-030-94893-1_25

Cited by 3 publications

(1 citation statement)

References 36 publications

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“…For this purpose, a unique image dataset is created and used to analyze the performance of different methods for detecting and recognizing different types of obstacles using three different architectures of deep learning algorithms [17]. The high precision of the experimental results shows that the development of egocentric applications can successfully contribute to maintaining the safety and cleanliness of sidewalks while reducing the accident rate of pedestrians [18].…”

Section: Literature Reviewmentioning

confidence: 99%

Assessment of Safe Access to Pedestrian Infrastructure Facilities in the City of Almaty, Kazakhstan

Tolegen¹,

Konbr²,

Karzhaubayeva³

et al. 2023

cea

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Currently, in all large and small cities in Kazakhstan, residential and public buildings are being actively built. It should be noted that the quantitative indicators of the construction of residential facilities prevail. The method applied to building residential facilities at the point and quarter increases the population density in urban areas. Increasing the number of residents requires assessing the levels of comfort for pedestrians at different speeds, the safety of sidewalks, and ensuring the accessibility of infrastructure facilities to people. The purpose of the study is to evaluate the quality of comfortable and safe conditions of pedestrian roads as a part of a district of Almaty. The assessment is based on the study of the presence and quality of elements and objects in the structures of transport roads and pedestrian sidewalks, and the determining level of pedestrian comfort is also applied (PCL). As a result of the study, the most problematic streets, the quality of pedestrian accessibility of extensive infrastructure facilities in each residential sector, and the main shortcomings and proposals for their elimination will be identified. The data obtained because of the study can be used in reconstruction, and urban area spatial planning concepts, allowing people to walk to most daily services and institutions, creating maximum opportunities to walk, reducing dependence on road transport, and contributing to the daily life of the community.

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Section: Literature Reviewmentioning

confidence: 99%

Assessment of Safe Access to Pedestrian Infrastructure Facilities in the City of Almaty, Kazakhstan

Tolegen¹,

Konbr²,

Karzhaubayeva³

et al. 2023

cea

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Performance Assessment of Fine-Tuned Barrier Recognition Models in Varying Conditions

Thoma,

Partaourides,

Sreedharan

et al. 2023

Lecture Notes in Computer Science

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Past, Present, and Future Perspectives on the Integration of AI Into Walkability Assessment Tools: A Systematic Review

Delavar,

Gamble,

Saldana-Ochoa

2024

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This study employs a systematic literature review (PRISMA methodology) to investigate the integration of Artificial Intelligence (AI) in walkability assessments conducted between 2012 and 2022. Analyzing 34 articles exploring data types, factors, and AI tools, the review emphasizes the value of utilizing diverse datasets, particularly street view images, to train supersized AI models. This approach fosters efficient, unbiased assessments and offers deep insights into pedestrian environment interactions. Furthermore, AI tools empower walkability assessment by facilitating mapping, scoring, designing pedestrian routes, and uncovering previously unconsidered factors. The current shift from large-scale spatial data analysis (allocentric perspective) to a ground-level view (egocentric perspective) and physical and perceptual features of walking introduces a subjective lens into current walkability assessment tools. However, the efficacy of current methods in addressing non-visual aspects of human perception and their applicability across diverse demographics remains debatable. Finally, the lack of integration of emerging technologies like virtual/augmented reality and digital twin leaves a significant gap in research, inviting further study to determine their efficacy in enhancing the current methods and, in general, understanding the interaction of humans and cities.

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Detection and Recognition of Barriers in Egocentric Images for Safe Urban Sidewalks

Cited by 3 publications

References 36 publications

Assessment of Safe Access to Pedestrian Infrastructure Facilities in the City of Almaty, Kazakhstan

Assessment of Safe Access to Pedestrian Infrastructure Facilities in the City of Almaty, Kazakhstan

Performance Assessment of Fine-Tuned Barrier Recognition Models in Varying Conditions

Past, Present, and Future Perspectives on the Integration of AI Into Walkability Assessment Tools: A Systematic Review

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